AI-Powered Data Analysis: A Practical Introduction

University of Michigan via Coursera

Coursera based on 13 ratings

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Overview

"AI-Powered Data Analysis: A Practical Introduction" is designed for professionals, analysts, and aspiring data scientists who want to leverage artificial intelligence for efficient and insightful data analysis. In this course, participants will explore the intersection of AI and data analysis, learning how to apply machine learning models, data preprocessing techniques, and AI tools to analyze and interpret large datasets. The course provides a hands-on approach to AI, covering essential techniques like supervised and unsupervised learning, feature engineering, data visualization, and model...

Syllabus

Laying the Groundwork: Data Foundations

This module teaches learners to understand and define data, utilize Generative AI for data acquisition, and effectively navigate various data formats and sources. Gain hands-on experience with real-world datasets.

Building Skills: Essential Practice

This module equips learners with fundamental data analysis skills, including selecting appropriate tools, cleaning and organizing data, performing statistical analyses, and creating visualizations, all while leveraging generative AI to enhance their capabilities.

Finishing Touches: Supporting Skills & Next Steps

This module equips learners with essential support skills such as version control, utilizing generative AI for technical assistance, and applying their data analysis knowledge to practical, domain-specific projects.